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Enhancing the performance of a rotational speed measurement system through data fusion

Wang, Lijuan, Yan, Yong, Reda, Kamel (2018) Enhancing the performance of a rotational speed measurement system through data fusion. Journal of Physics: Conference Series, 1065 . pp. 1-4. ISSN 1742-6588. (doi:10.1088/1742-6596/1065/7/072024) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:77849)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL:
http://dx.doi.org/10.1088/1742-6596/1065/7/072024

Abstract

Electrostatic sensors with a single electrode or double electrodes have been applied for rotational speed measurement. In order to improve the performance of the rotational speed measurement system based on double electrostatic sensors, a data fusion algorithm is incorporated in the system. Two independent signals are accessible from the electrostatic sensor with double electrodes. From these signals two independent rotational speed measurements are obtained through auto-correlation processing of each signal and the third rotational speed measurement is also achieved by cross-correlating the two signals. A data fusion algorithm is then applied to optimally combine the three measurements. The system with the data fusion algorithm is capable of producing more accurate and more robust measurements than previous double-sensor system with a wider measurement range. Experimental results suggest that the relative error of the improved system is mostly within ±0.5% over the speed range of 200 rpm - 3000 rpm.

Item Type: Article
DOI/Identification number: 10.1088/1742-6596/1065/7/072024
Uncontrolled keywords: Rotational speed measurement
Subjects: T Technology > TA Engineering (General). Civil engineering (General) > TA165 Engineering instruments, meters etc. Industrial instrumentation
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User: Lijuan Wang
Date Deposited: 25 Oct 2019 16:34 UTC
Last Modified: 04 Mar 2024 17:46 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/77849 (The current URI for this page, for reference purposes)

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